Fix 627

fluid/DeepASR/data_utils/augmentor/tests/__init__.py

@@ -0,0 +1,7 @@
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import data_utils.augmentor.trans_mean_variance_norm as trans_mean_variance_norm
+import data_utils.augmentor.trans_add_delta as trans_add_delta
+import data_utils.augmentor.trans_splice as trans_splice

fluid/DeepASR/data_utils/data_reader.py

@@ -62,10 +62,22 @@ class SampleInfoBucket(object):
  label_bin_paths (list|tuple): Files containing the binary label data.
  label_desc_paths (list|tuple): Files containing the description of
  samples' label data.
+ split_perturb(int): Maximum perturbation value for length of 
+ sub-sentence when splitting long sentence.
+ split_sentence_threshold(int): Sentence whose length larger than 
+ the value will trigger split operation.
+ split_sub_sentence_len(int): sub-sentence length is equal to 
+ (split_sub_sentence_len + rand() % split_perturb).
  """
 
- def __init__(self, feature_bin_paths, feature_desc_paths, label_bin_paths,
- label_desc_paths):
+ def __init__(self,
+ feature_bin_paths,
+ feature_desc_paths,
+ label_bin_paths,
+ label_desc_paths,
+ split_perturb=50,
+ split_sentence_threshold=512,
+ split_sub_sentence_len=256):
  block_num = len(label_bin_paths)
  assert len(label_desc_paths) == block_num
  assert len(feature_bin_paths) == block_num
@@ -76,6 +88,10 @@ def __init__(self, feature_bin_paths, feature_desc_paths, label_bin_paths,
  self._feature_desc_paths = feature_desc_paths
  self._label_bin_paths = label_bin_paths
  self._label_desc_paths = label_desc_paths
+ self._split_perturb = split_perturb
+ self._split_sentence_threshold = split_sentence_threshold
+ self._split_sub_sentence_len = split_sub_sentence_len
+ self._rng = random.Random(0)
 
  def generate_sample_info_list(self):
  sample_info_list = []
@@ -102,12 +118,45 @@ def generate_sample_info_list(self):
  label_start = int(label_desc_split[2])
  label_size = int(label_desc_split[3])
  label_frame_num = int(label_desc_split[4])
-
- sample_info_list.append(
- SampleInfo(feature_bin_path, feature_start, feature_size,
- feature_frame_num, feature_dim, label_bin_path,
- label_start, label_size, label_frame_num))
-
+ assert feature_frame_num == label_frame_num
+
+ if self._split_sentence_threshold == -1 or \
+ self._split_perturb == -1 or \
+ self._split_sub_sentence_len == -1 \
+ or self._split_sentence_threshold >= feature_frame_num:
+ sample_info_list.append(
+ SampleInfo(feature_bin_path, feature_start,
+ feature_size, feature_frame_num, feature_dim,
+ label_bin_path, label_start, label_size,
+ label_frame_num))
+ #split sentence 
+ else:
+ cur_frame_pos = 0
+ cur_frame_len = 0
+ remain_frame_num = feature_frame_num
+ while True:
+ if remain_frame_num > self._split_sentence_threshold:
+ cur_frame_len = self._split_sub_sentence_len + \
+ self._rng.randint(0, self._split_perturb)
+ if cur_frame_len > remain_frame_num:
+ cur_frame_len = remain_frame_num
+ else:
+ cur_frame_len = remain_frame_num
+
+ sample_info_list.append(
+ SampleInfo(
+ feature_bin_path, feature_start + cur_frame_pos
+ * feature_dim * 4, cur_frame_len * feature_dim *
+ 4, cur_frame_len, feature_dim, label_bin_path,
+ label_start + cur_frame_pos * 4, cur_frame_len *
+ 4, cur_frame_len))
+
+ remain_frame_num -= cur_frame_len
+ cur_frame_pos += cur_frame_len
+ if remain_frame_num <= 0:
+ break
+
+ print("generate_sample_info_list size ", len(sample_info_list))
  return sample_info_list
 
 
@@ -125,7 +174,7 @@ class DataReader(object):
  label_file_list (str): File containing paths of label data file and 
  corresponding description file.
  drop_frame_len (int): Samples whose label length above the value will be
- dropped.
+ dropped.(Using '-1' to disable the policy)
  process_num (int): Number of processes for processing data.
  sample_buffer_size (int): Buffer size to indicate the maximum samples 
  cached.
@@ -149,7 +198,7 @@ def __init__(self,
  sample_buffer_size=1024,
  sample_info_buffer_size=1024,
  batch_buffer_size=1024,
- shuffle_block_num=1,
+ shuffle_block_num=10,
  random_seed=0,
  verbose=0):
  self._feature_file_list = feature_file_list
@@ -253,11 +302,21 @@ def read_bytes(fpath, start, size):
  sample_info.feature_start,
  sample_info.feature_size)
 
+ assert sample_info.feature_frame_num * sample_info.feature_dim * 4 \
+ == len(feature_bytes), \
+ (sample_info.feature_bin_path,
+ sample_info.feature_frame_num,
+ sample_info.feature_dim,
+ len(feature_bytes))
+
  label_bytes = read_bytes(sample_info.label_bin_path,
  sample_info.label_start,
  sample_info.label_size)
 
- assert sample_info.label_frame_num * 4 == len(label_bytes)
+ assert sample_info.label_frame_num * 4 == len(label_bytes), (
+ sample_info.label_bin_path, sample_info.label_array,
+ len(label_bytes))
+
  label_array = struct.unpack('I' * sample_info.label_frame_num,
  label_bytes)
  label_data = np.array(
@@ -282,7 +341,8 @@ def read_bytes(fpath, start, size):
  time.sleep(0.001)
 
  # drop long sentence
- if self._drop_frame_len >= sample_data[0].shape[0]:
+ if self._drop_frame_len == -1 or \
+ self._drop_frame_len >= sample_data[0].shape[0]:
  sample_queue.put(sample_data)
 
  out_order[0] += 1

fluid/DeepASR/train.py

@@ -176,7 +176,7 @@ def test(exe):
 
  # train data reader
  train_data_reader = reader.DataReader(args.train_feature_lst,
- args.train_label_lst)
+ args.train_label_lst, -1)
  train_data_reader.set_transformers(ltrans)
  # train
  for pass_id in xrange(args.pass_num):